This section is intended to introduce the reader to various aspects of art that may be related to various aspects of the subject matter described and/or claimed below. This discussion is believed to be helpful in providing the reader with background information to facilitate a better understanding of the various aspects of the present disclosure. Accordingly, it should be understood that these statements are to be read in this light, not as admissions of prior art.
The present disclosure relates generally to techniques for using nuclear magnetic resonance (NMR) to acquire data indicative of the properties of hydrocarbons and, more specifically, to an NMR measurement system for acquiring data of the properties of live oils at temperatures and pressures reflective of realistic reservoir conditions.
Oil and gas exploration and production are very expensive operations. Any knowledge about the formations that can help reduce the unnecessary waste of resources in well drilling will be invaluable. Therefore, the oil and gas industry has developed various tools capable of determining and predicting earth formation properties. Among different types of tools, nuclear magnetic resonance (NMR) instruments have proven to be invaluable. NMR instruments can be used to determine formation properties, such as the fractional volume of pore space and the fractional volume of mobile fluid filling the pore space.
The introduction of pulsed nuclear magnetic resonance (NMR) logging tools in the early 1990's brought to the industry new capabilities for characterization of oil and gas bearing reservoirs. These tools employ diffusion encoded pulse sequences that can be used to separate oil, gas, and water signals based on contrasts in the molecular diffusion coefficients of the fluids (See, Freedman et al., “A New Method of Fluid Characterization in Reservoir Rocks: Experimental Confirmation and Simulation Results,” SPE Paper 63214 (2000); see also Freedman et al., “Fluid Characterization Using Nuclear Magnetic Resonance Logging,” Petrophysics, vol. 45, p. 241-250 (2004)). Thus, NMR diffusion-based fluid typing provided the industry with a tool for identifying oil and gas reservoirs. Additionally, NMR logging provided the density-magnetic resonance method for identifying and evaluating gas-bearing zones (See Freedman et al., “Combining NMR and Density Logs for Petrophysical Analysis in Gas Bearing Formations,” SWPLA, 39th Annual Logging Symposium (1998)).
In general, NMR provides an excellent non-invasive technique for studying the microscopic molecular interactions in fluid systems and, therefore, it provides a means for predicting molecular and macroscopic petroleum fluid properties. The temperature and pressure dependence of molecular interactions governing the NMR response provides an understanding of the dynamical processes in such systems. Furthermore, NMR measurements of relaxation time and diffusion coefficients of fluids are related to macroscopic properties which are strongly temperature and pressure dependent. However, in spite of the successes in fluid typing and the prediction of near wellbore reservoir fluid volumes, the accurate prediction of reservoir fluid properties (e.g., viscosity, fluid density, molecular composition, saturates, aromatics, resins, and asphaltene (SARA) fractions, gas-oil ratio (GOR), etc.) using NMR-related techniques has made little progress.
It is believed that the lack of progress in this regard can be attributed to several factors. First, crude oils are complex and variable mixtures of organic and inorganic molecules containing different amounts and types of dissolved gas molecules. This complexity cannot be accurately described by the simple idealized models that are commonly used in the industry (See Freedman et al., “A Modern Method for Using Databases to Obtain Accurate Solutions to Complex Reservoir Characterization Problems,” SPE Reservoir Evaluation and Engineering, vol. 15, pp. 453-461 (2012)). It became realized that accurate prediction of fluid properties from NMR required a model-independent approach to address the inherent complexity of crude oils. Second, there were no known extensive databases of NMR, PVT (pressure/volume/temperature), and physical properties data acquired on live oils at realistic reservoir conditions. Such databases are important for the development and validation of the accuracy of NMR-based predictive methods.
The problem of reservoir fluid complexity was at least partly addressed in Freedman et al., “New Approach for Solving Inverse Problems Encountered in Well-Logging and Geophysical Applications,” Petrophysics, vol. 47, pp. 93-111 (2006), which describes a model-independent method for accurately solving inverse problems for complex systems. This method uses a general model-independent mapping function to approximate the unknown functional relationship between the NMR measurements and the fluid properties to be predicted. The mapping function can be uniquely determined from a database of NMR and fluid properties measurements and can be expressed in analytical form as a summation of Gaussian radial basis functions (RBF). In summary, this model-independent method addresses the notion that while crude oils are too complex to be accurately described by simple models, the physics are contained in the database and can be represented by a general non-linear mapping function. As described in the above-referenced Freedman 2006 publication, this mapping function methodology was tested on a small database of dead oils (oils without dissolved gases) and obtained encouraging results from the predictions of viscosity and molecular composition. Accordingly, the results showed that the foregoing method has the potential to predict accurate fluid properties of live oils from a database of NMR, PVT, and fluid properties measurements.
Additional studies and experimentation were performed using an NMR measurement system in a laboratory setting to assess the viability of the above-described mapping function methodology when applied to a database of live oils, as described in Anand et al., “New Method for Predicting Properties of Live Oils from NMR,” Petrophysics, vol. 53, pp. 256-271 (2012). The NMR measurement system was installed by Schlumberger Technology Corporation and included a 2 MHz spectrometer (e.g., a commercial Resonance Instruments Maran spectrometer). The NMR measurement system also included a pressure cell for making NMR measurements on single phase live oils (e.g., based on a commercial pressure model by Temco, Inc.). This study provided encouraging results showing that important fluid properties, including molecular composition, viscosity, and SARA fractions could be predicted with reasonable accuracy from a relatively sparse database using this mapping function method. However, the installed commercial system described in Anand et al. 2012 had significant limitations and was not a viable system for the acquisition of an extensive database of NMR measurements at realistic conditions of temperature and pressure. For instance, the Anand et al. 2012 NMR measurement system was restricted to pressure and temperature limits of about 10 kpsi and 110 degrees C., both of which falls far short of the 25 kpsi and 175 degrees centigrade (C) representative of real conditions in some worldwide oil reservoirs. Another serious limitation of the Anand et al. 2012 system was its relatively low signal-to-noise ratio (SNR) (e.g., 15:1), which required very long measurement times (e.g., more than 12 hours for pulsed field gradient diffusion measurements) at each pressure and temperature.